Python Medical-Image-Triage-and-Classification-System-Based-on-COVID-19-CT-and-X-ray-Scan-Dataset Resources

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deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.

Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"

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IDA Pattern Search by Argus Cyber Security Ltd. The IDA Pattern Search plugin adds a capability of finding functions according to bit-patterns into th

Python desktop application to create, distribute, discover, and run codegames

Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size and relatively competitive performance compared to BERT and its variants. For further accelerating the research of the Chinese pre-trained model, the Joint Laboratory of HIT and iFLYTEK Research (HFL) has released the Chinese ELECTRA models based on the official code of ELECTRA. ELECTRA-small could reach similar or even higher scores on several NLP tasks with only 1/10 parameters compared to BERT and its variants.

Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.

A desktop application for JupyterLab, based on Electron.

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pcnaDeep: a deep-learning based single-cell cycle profiler with PCNA signal Welcome! pcnaDeep integrates cutting-edge detection techniques with tracki

motor-system Introduction A code copied from google-research which named motion-imitation was rewrited with PyTorch. More details can get from this pr

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